nimare.meta.cbma.kernel.KDAKernel

class KDAKernel(r=6, value=1)

Generate KDA modeled activation images from coordinates.

Parameters:

• r (int, optional) – Sphere radius, in mm.
• value (int, optional) – Value for sphere.

Methods

get_params(self[, deep])	Get parameters for this estimator.
load(filename[, compressed])	Load a pickled class instance from file.
save(self, filename[, compress])	Pickle the class instance to the provided file.
set_params(self, \*\*params)	Set the parameters of this estimator.
transform(self, dataset[, mask, masked])	Generate KDA modeled activation images for each Contrast in dataset.

get_params(self, deep=True)

Get parameters for this estimator.

Parameters:deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns:params – Parameter names mapped to their values. Return type:mapping of string to any

classmethod load(filename, compressed=True)

Load a pickled class instance from file.

Parameters:

• filename (str) – Name of file containing object.
• compressed (bool, optional) – If True, the file is assumed to be compressed and gzip will be used to load it. Otherwise, it will assume that the file is not compressed. Default = True.

Returns:

obj – Loaded class object.

Return type:

class object

save(self, filename, compress=True)

Pickle the class instance to the provided file.

Parameters:

• filename (str) – File to which object will be saved.
• compress (bool, optional) – If True, the file will be compressed with gzip. Otherwise, the uncompressed version will be saved. Default = True.

set_params(self, **params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Returns: Return type:self

transform(self, dataset, mask=None, masked=False)

Generate KDA modeled activation images for each Contrast in dataset. Differs from MKDA images in that binary spheres are summed together in map (i.e., resulting image is not binary if coordinates are close to one another).

Parameters:

• dataset (nimare.dataset.Dataset or pandas.DataFrame) – Dataset for which to make images. Can be a DataFrame if necessary.
• mask (img_like, optional) – Only used if dataset is a DataFrame.
• masked (bool, optional) – Return an array instead of a niimg.

Returns:

imgs – A list of modeled activation images (one for each of the Contrasts in the input dataset).

Return type:

list of nibabel.Nifti1Image